Join NVIDIA, a leader in AI and accelerated computing, and drive the future of silicon productization. Our team focuses on power and performance optimization, ensuring NVIDIA's cutting-edge silicon products are ready for production. You'll work across architecture, design, silicon, firmware, and software to shape how products are configured and shipped.

This role offers a unique opportunity to influence the development of new silicon, from initial design through to large-scale production. If you're passionate about working with new silicon and leveraging data and AI to solve complex engineering challenges, we encourage you to apply.

Spearhead silicon power productization, encompassing test strategy, feature readiness, characterization, and optimization from pre-silicon stages through to production. Collaborate with architecture and design teams to enhance designs, validate features, and develop production-ready solutions. Characterize and fine-tune controller performance across diverse workloads, operating conditions, silicon variations, and product power/thermal limits. Develop robust power and performance models and methodologies to inform silicon binning, product specifications, and customer guidance. Utilize AI/ML and data-driven approaches to analyze characterization and telemetry data, identify anomalies, and accelerate debugging across hardware and software components.

A Bachelor's or Master's degree in Electronics Engineering, Electrical Engineering, or a related field, or equivalent practical experience is required. Demonstrate at least 3 years of hands-on experience in silicon bring-up, characterization, validation, productization, or a similar hardware domain. Possess a solid understanding of silicon power and performance factors, including process technology, voltage, frequency, workloads, and operating conditions. Showcase experience with system-level hardware debugging and managing interactions between silicon, board hardware, firmware, and software. Exhibit strong data analysis and problem-solving capabilities, with the ability to translate measurements into testable hypotheses.